Modeling of Residential Property Prices Index Using Committees of Artificial Neural Networks for Pigs the European-G8 and Poland

• Autorzy: Radosław Wiśniewski
• Języki publikacji: EN

Abstrakty

EN

This paper develops models of residential property prices indices for PIGS, the European-G8 and Poland using a committee of artificial neural networks approach. Quarterly time series data are applied for testing and the empirical results suggest that population growth, unemployment rate, final consumption expenditure, net national income (ANNI), household final consumption expenditure, long-term interest rates, HICP rate of change of housing, water, electricity, gas and other fuels, HICP housing services, HICP actual rentals for housing, and HICP maintenance and repair of the dwelling are the major determinants of the residential property price index in PIGS, the European-G8 and Poland. The developed models show that the economic and financial situation in a given country affects the residential property markets. Residential property markets are connected, despite the fact that they are situated in different parts of Europe. The economic and financial crisis in the countries of the PIGS group affects not only the PIGS markets but also the real estate markets of the European-G8 and Poland. The results also suggest that a methodology based on a committee of artificial neural networks has the ability to learn, generalize, and converge the residential property prices index3.

Słowa kluczowe

EN

Real estate prices; Real estate; Neural networks; Harmonised Index of Consumer Prices (HICP)

PL

Ceny nieruchomości; Nieruchomości; Sieci neuronowe; Zharmonizowany wskaźnik cen konsumpcyjnych

• Czasopismo: Argumenta Oeconomica
• Rocznik: 2017
• Numer: nr 1 (38)
• Strony: 145--194

Twórcy

autor

Radosław Wiśniewski

• University of Warmia and Mazury in Olsztyn, Poland

Bibliografia

• Adair, A., Mcgreal, S., Smyth, A., Cooper, J., Ryley, T., House Prices and Accessibility: The Testing of Relationships within the Belfast Urban Area, "Housing Studies", 15(5), pp.699-716, 2000.
• Adams, Z., Füss, R., Macroeconomic Determinants of International Housing Markets, "Journal of Housing Economics", 19 (1), pp. 38-50, 2010.
• Agnello, L., Schuknecht, L., Booms and Busts in Housing Markets: Determinants and Implications, "Journal of Housing Economics", 2011, doi:10.1016/j.jhe.2011.04.001.
• Ahearn, A. G., Ammer, J., Doyle, B. M., Kole, L. S., Martin, R. F., House Prices and Monetary Policy: A Cross-country Study, "International Finance Discussion Paper" No. 841, Board of Governors of the Federal Reserve System, 2005.
• Aizenman, J., Jinjarak, Y., Current Account Patterns and National Real Estate Markets, "Journal of Urban Economics" 66 (2009), pp. 75-89, 2009.
• Amabile, R., Rosato, P., The Use of Neural Networks in the Spatial Analysis of Property Values [in:] Proceedings of the Sixth Joint Conference on Agriculture, Food, and the Environment, Minneapolis, Minnesota, August 31-September 2, 1998.
• Arestis, P., McCombie, J. S. L., Vickerman, R. W., Thirlwall, A. P., Growth and Economic Development: Essays in Honour of A. P. Thirlwall, pp. 185. Edward Elgar Publishing, 2006.
• Bao, H. X. H., Wan, A. T. K., On the Use of Spline Smoothing in Estimating Hedonic Housing Price Models: Empirical Evidence Using Hong Kong Data, "Real Estate Economics", 32(3), pp. 487-507, 2004.
• Berg, L., Price Indexes for Multi-dwelling Properties in Sweden, "Journal of Real Estate Research", p. 27, 1, 2005.
• Bin, O., A Prediction Comparison of Housing Sales Prices by Parametric versus Semi-parametric Regressions, "Journal of Housing Economics", 13, pp. 68-84, 2004.
• Bishop, C., Neural Networks for Pattern Recognition. University Press, Oxford, 1995.
• Borst, R. A., Artificial Neural Networks in Mass Appraisal, "Journal of Property Tax Assessment &Administration", 1(2), pp. 5-15, 1995.
• Borst, R. A., McCluskey, W., The Role of Artificial Neural Networks in the Mass Appraisal of Real Estate. Paper presented to the Third European Real Estate Society Conference, Belfast, June 26-28 1996.
• Ceron, J. A., Suarez, J., Hot and Cold Housing Markets: International Evidence, CEPR Discussion Papers 2006, 5411.
• Chan, H. L., Lee, S. K.,Woo, K. Y., Detecting Rational Bubbles in the Residential Housing Markets in Hong Kong. "Economics Modelling", 18, pp. 61-73, 2001.
• Cho, B., Kim, J. H., Combining Multiple Neural Networks by Fuzzy Integral for Robust Classification, "IEEE Transactions on Systems Man and Cybernetics" 25, pp. 380-384, 1995.
• Do, A. Q., Grudnitski, G., A Neural Network Approach to Residential Property Appraisal, "The Real Estate Appraiser", pp. 38-45, 1992.
• Ducaa, J. V., Muellbauerc, J., Murphyd, A., Housing Markets and the Financial Crisis of 2007-2009: Lessons for the Future, "Journal of Financial Stability" 6 (2010) pp. 203-217, 2009.
• Economist. 2010a. The PIIGS that Won't Fly. A Guide to the Euro-zone's Troubled Economies, "The Economist" 18 May 2010.
• http://www.economist.com/node/15838029. Economist. 2010b. The Irish Problem, "The Economist", 16 November 2010.
• http://www.economist.com/ blogs/charlemagne/2010/11/ireland_and_euro.
• Englund, P., Ioannides, Y. M., House Price Dynamics: An International Empirical Perspective, "Journal of Housing Economics" 6, pp. 119-136, 1997.
• Evans, A., James, H., Collins, A., Artificial Neural Networks: An Application to Residential Valuation in the UK, "Journal of Property Valuation & Investment", 11, pp. 195-204, 1993.
• Fan, G., Ong, Z. S. E., Koh, H. C., Determinants of House Price: A Decision Tree Approach, "Urban Studies", 43(12), pp. 2301-2315, 2006.
• Filho, C. M., Bin, O., Estimation of Hedonic Price Functions via Additive Nonparametric Regression, "Empirical Economics", 30(1), pp. 93-114, 2005.
• Fletcher, M., Mangan, J., Raeburn, E., Comparing Hedonic Models for Estimating and Forecasting House Prices, "Property Management", 22(3), pp. 189-200, 2004.
• Foresee, F. D., Hagan, M. T., Gauss-Newton Approximation to Bayesian Learning, "Proceedings of the IEEE International Joint Conference on Neural Networks", 1997, pp. 1930-1935, 1997.
• Ge, J. X., Runeson, G., Lam, K. C., Forecasting Hong Kong Housing Prices: An Artificial Neural Network Approach, Methodologies in Housing Research Conference, 2003.
• Ge, X. J., Runeson, G., Modeling Property Prices Using Neural Network Model for Hong Kong, "International Real Estate Review" Vol. 7, no. 1, pp. 121-138, 2004.
• Geman, S., Bienenstock E., Doursat R., Neural Networks and the Bias-variance Dilemma, "Neural Computation" 4, p. 1-58, 1992.
• Girouard, N., Kennedy, M., van den Nord, P., Andre, C., Recent House Price Developments. OECD Economics Department working papers, no. 475, 2006.
• Goodhart, C., Beyond Current Policy Frameworks, Working Papers 189, BIS, 2005.
• Haykin, S., Neural Networks: A Comprehensive Foundation. New York: Macmillan Publishing, New York, 1994.
• Heskes, T., Balancing between Bagging and Bumping [in:] Mozer, M. C., Jordan, M. I., Petsche, T. (eds.), Advances in Neural Information Processing Systems, Vol. 9, pp. 466-472. MIT Press, 1997.
• Hiebert, P., Sydow, M. What Drives Returns to Euro Area Housing? Evidence from a Dynamic Dividend-discount Model, "Journal of Urban Economics", doi: 10.1016/ j.jue.2011.03.001, 2011.
• Huia, E. C. M., Yua, C. K. W., Ip Wai-Cheung, Jump Point Detection for Real Estate Investment Success, "Physica A", 389, pp. 1055-1064, 2010.
• Hwang, M., Quigley, J., Economic Fundamentals in Local Housing Markets: Evidence from US Metropolitan Regions, "Journal of Regional Science" 46 (3), pp. 425-453, 2006.
• Iacovello, M., Minetti, R., Financial Liberalization and the Sensitivity of House Prices to Monetary Policy: Theory and Evidence, "The Manchester School" 71 (1), pp. 20-34, 2003.
• IMF, What Explains the Recent Run-up in House Prices? [in:] World Economic Outlook, September 2004.
• Jacobs, R. A., Bias/Variance Analyses of Mixtures-of-Experts Architectures, "Neural Computation" 9 (2), p. 369-383, 1997.
• Janssen, C., Söderberg, B. Zhou, J., Robust Estimation of Hedonic Models of Price and Income for Investment Property, "Journal of Property Investment & Finance", 19(4), pp. 342-360, 2001.
• Jud, D., Winkler, D. 2002. The Dynamics of Metropolitan Housing Prices, "Journal of Real Estate Research 23 (1), pp. 29-45, 2002.
• Kaklauskasa, A., Kelpsienea, L., Zavadskasb, E. K., Bardauskienea, D., Kaklauskasa, G., Urbonasa, M., Sorakasa, V., Crisis Management in Construction and Real Estate: Conceptual Modeling at the Micro-, Meso- and Macro-levels, "Land Use Policy" 28 (2011) pp. 280-293, 2011.
• Kauko, T., Hooimeijer, P., Hakfoort, J., Capturing Housing Market Segmentation: An Alternative Approach Based on Neural Network Modeling, "Housing Studies", 17(6), pp. 875-894, 2002.
• Kauko, T., On Current Neural Network Applications Involving Spatial Modelling of Property Prices, "Journal of Housing and the Built Environment", 18(2), pp. 159-181, 2003.
• Kasparova, D., White, M., The Responsiveness of House Prices to Macroeconomic Forces: A Cross-country Comparison, "European Journal of Housing Policy" 1 (3), pp. 385-416, 2001.
• Kennedy, N., Andersen, P., Housing Saving and the Real House Prices: An International Prospective, BIS Working Paper. p. 20, 1994.
• Kershaw, P., Rossini, P., Using Neural Networks to Estimate Constant Quality House Price Indices. Fifth Annual Pacific-Rim Real Estate Society Conference Kuala Lumpur, Malaysia, 26-30 January 1999.
• Kestens, Y., Theriault, M., Rosier, F. D., Heterogeneity in Hedonic Modelling of House Prices: Looking at Buyers' Household Profiles, "Journal of Geographical Systems", 8(1), pp. 61-96, 2006.
• Khalafallah, A. 2008. Neural Network Based Model for Predicting Housing Market, "Tsinghua Science And Technology", Volume 13, Number S1, pp. 325-328, October 2008.
• Kim, S. P., Sanchez, J. C., Erdogmus, D., Rao, Y. N., Wessberg, J., Principe, J. C., Nicolelis, M. 2003. Divide-and-conquer Approach for Brain Machine Interfaces: Nonlinear Mixture of Competitive Linear Models, "Neural Networks" 16, pp. 865-871, 2003.
• Kim, K., Park, J., Segmentation of the Housing Market and Its Determinants: Seoul and Its Neighbouring New Towns in Korea, "Australian Geographer", 36(2), pp. 221-232, 2005.
• Kittler, J., Hatef, M., Duin, R. P. W., Matas, J. 1998. On Combining Classifiers, "IEEE Trans Pattern Analysis and Machine Intelligence" 20, pp. 226-239, 1998.
• Koetter, M., Poghosyan, T. Real Estate Prices and Bank Stability, "Journal of Banking&Finance" 34, pp. 1129-1138, 2010.
• Kontrimas, V. Verikas, A. 2011. The Mass Appraisal of the Real Estate by Computational Intelligence, "Applied Soft Computing" 11, pp. 443-448, 2011.
• Kotlowski, D. J., The European Union: from Jean Monnet to the Euro, p. 36. Ohio University Press, 2000.
• Krogh, A., Vedelsby, J. 1995. Neural Network Ensembles, Cross Validation, and Active Learning [in:] Tesauro, G., Touretzky, S. D., Leen, K. T. (eds.), Advances in Neural Information Processing Systems, Vol. 7, MIT Press, pp. 231-238, 1995.
• Lecat, R., Mesonnier, J. S., What Role Do Financial Factors Play in House Price Dynamics, Banque De France Bulletin. p. 134, 2005.
• Lenk, M. M., Worzala, E. M. Silva, A., High-tech Valuation: Should Artificial Neural Networks Bypass the Human Valuer, "Journal of Property Valuation and Investment", 15, pp. 8-26, 1997.
• Liu, C. L., Classifier Combination Based on Confidence Transformation, "Pattern Recognition" 38, pp. 11-28, 2005.
• McCluskey, W., Predictive Accuracy of Machine Learning Models for Mass Appraisal of Residential Property, "New Zealand Valuer's Journal", pp. 41-47, 1996.
• McCluskey, W., Dyson, K., McFall, D., Anand, S., Mass Appraisal for Property Taxation: An Artificial Intelligence Approach, "Land Economics Review", Vol 2, No 1, pp. 25-32, 1996.
• McGreal, S., Adair, A., Mcburney, D., Patterson, D., Neural Networks: The Prediction of Residential Values, "Journal of Property Valuation and Investment", 16, pp. 57-70, 1998.
• Meese, R., Wallace, N., House Price Dynamics and Market Fundamentals: The Parisian Housing Market, "Urban Studies", 40(5-6), pp. 1027-1045, 2003.
• Merz, C. J., Pazzani, M. J. 1997. Combining Neural Network Regression Estimates with Regularised Linear Weights [in:] Mozer, C. M., Jordan, M. I., Petsche, T., (eds.), Advances in Neural Information Processing Systems, pp. 564-570. MIT Press, 1997.
• Muellbauer, J., Murphy, A., Booms and Busts in the UK Housing Market, "Economic Journal" 107 (445), pp. 1701-1727, 1997.
• Ogwang, T., Wang, B., The Hedonic Price Function for a Northern BC Community, "Social Indicators Research", 61, pp. 285-296, 2003.
• Opitz, D. W., Shavlik, J. W., Actively Searching for an Effective Neural Network Ensemble, "Connection Science", Vol. 8, nr 3 & 4, pp. 337-353, 1996.
• Pagourtzi, E., Assimakopoulos, V., Hatzichristos, T., French, N., Real Estate Appraisal: A Review of Valuation Methods, "Journal of Property Investment & Finance", 21(4), pp. 383-401, 2003.
• Parker, J. A., Comments and Discussion On: Case KE. Real Estate and the Macroeconomy, "Brookings Papers on Economic Activity" 2, pp. 146-159, 2000.
• Renaud, B., The 1985 to 1994 Global Real Estate Cycle: An Overview, "Journal of Real Estate Literature" 5, pp. 13-44, 1997.
• Rossini, P. A., 1997a, Application of Artificial Neural Networks to the Valuation of Residential Property, 3rd Pacific Rim Real Estate Society Conference, New Zealand ,1997.
• Rossini, P. A., 1997b, Artificial Neural Networks versus Multiple Regression in the Valuation of Residential Property, "Australian Land Economics Review", Vol 3, No 1, November 1997.
• Rossini, P. A. 1997c. Improving the Results of Artificial Neural Network Models for Residential Valuation. 4th Pacific Rim Real Estate Society Conference, Perth 1998.
• Rossini, P. A., Improving the Results of Artificial Neural Network Models for Residential Valuation [in:] Proceedings of Fourth annual Pacific Rim Real Estate Society Conference, 1998.
• Shaaf, M., Erfani, G., Air Pollution and the Housing Market: A Neural Network Approach, "International Advances in Economic Research", 4(2): pp. 484-495, 1996.
• Sollich, S., Krogh, A., Learning with Ensembles: How Over-fitting Can Be Useful [in:] Touretzky, S. D., Mozer, C. M., Hasselmo, H. E. (eds.), Advances in Neural Information Processing Systems, Vol. 8, pp. 190-197. MIT Press, 1996.
• StatSoft, Inc., STATISTICA (data analysis software system), version 9.0. www.statsoft.com, 2009.
• Stevenson, S., New Empirical Evidence on Heteroscedasticity in Hedonic Housing Models, "Journal of Housing Economics", 13, pp. 136-153, 2004.
• Tresp, V., Taniguchi, M., Combining Estimators Using Non-constant Weighting Functions [in:] Tesauro, G., Touretzky, S. D., Leen, K. T., (eds.), Advances in Neural Information Processing Systems, Vol. 7. MIT Press, 1995.
• Tsatsaronis, K., Zhu, H., What Drives Housing Price Dynamics: Cross Country Evidence, "BIS Quarterly Review March", pp. 65-78, 2004.
• Verikas, A., Lipnickas, A., Malmqvist, K., Bacauskiene, M., Gelzinis, A. 1999. Soft Combination of Neural Classifiers: A Comparative Study, "Pattern Recognition Letters" 20, pp. 429-444, 1999.
• Verikas, A., Lipnickas, A., Fusing Neural Networks through Space Partitioning and Fuzzy Integration, "Neural Processing Letters" 16, pp. 53-65, 2002.
• Verikas, A., Lipnickas, A., Malmqvist, K., Selecting Neural Networks for a Committee Decision, "International Journal of Neural Systems" 12, pp. 351-361, 2002.
• Wilson, I. D., Paris, S. D., Ware, J. A., Jenkins, D. H., Residential Property Price Time Series Forecasting with Neural Networks, "Knowledge-Based Systems", 15, pp. 335-341, 2002.
• Wiśniewski, R., Modular Neural Networks. Proceedings of the 4th National Conference on Methods and Computer Systems in Research and Engineering Design. Wyd. AG-H, Politechnika Krakowska, Uniwersytet Jagielloński, pp. 253-264, Kraków, 2003.
• Wiśniewski, R., Modelling the Real Estate Market Using MSN, "Journal of the Polish Real Estate Scientific Society", Vol. I, pp. 210-220. TNN, Olsztyn, 2004.
• Wiśniewski, R., Multidimensional Forecasting of the Value of a Real Estate, "Dissertations and Monographs" no. 124, UWM, 2008.
• Wong, B. K., Selvi, Y., Neural Network Applications in Finance: A Review and Analysis of Literature (1990-1996), "Information & Management" 34 (1998), pp. 129-139, 1998.
• Worzala, E., Lenk, M., Silva, A., An Exploration of Neural Networks and Its Application to Real Estate Valuation, "The Journal of Real Estate Research", Vol. 10, no. 2, 1995.
• Quigley, J., Real Estate and the Asian Crisis, "Journal of Housing Economics" 10, pp. 129-161, 2001.

Identyfikatory

DOI

10.15611/aoe.2017.1.06